Testing started at 上午 11:10 ...
F:\python\Anaconda3\envs\tensorflow\python.exe "F:\Program Files\PyCharm 2018.3.3\helpers\pycharm_jb_pytest_runner.py" --path F:/WorkSpace/python/Information-Extraction-Chinese-master/RE_BGRU_2ATT/test_GRU.py
Launching pytest with arguments F:/WorkSpace/python/Information-Extraction-Chinese-master/RE_BGRU_2ATT/test_GRU.py in F:\WorkSpace\python\Information-Extrac

执行thulac.cut('《一本书看懂中国人》是2009年新世界出版社出版的图书')得到[['《', 'w'], ['一本书看懂中国人', 'id'], ['》', 'w'], ['是', 'v'], ['2009年', 't'], ['新', 'a'], ['世界', 'n'], ['出版社', 'n'], ['出版', 'v'], ['的', 'u'], ['图书', 'n']]

一本书看懂中国人的词性标注为 id，在readme的词性解释中不存在，请更新。

图片上传不了，直接贴log了。
d:\programing\ml\thulac\thulac-master\include\cb_ngram_feature.h(37): error C2039: “dat”: 不是“thulac::NGramFeature”的成员
d:\programing\ml\thulac\thulac-master\include\cb_ngram_feature.h(14): note: 参见“thulac::NGramFeature”的声明
d:\programing\ml\thulac\thulac-master\include\cb_ngram_feature.h(62): warning C4018: “<”: 有符号/无符号不匹配
d:\programing\ml\thulac\thulac-master\include\cb_ngram_

not a bug report per se

I'm wondering how spacy/chinese models compares with the stanza project?
Stanza already provides chinese support with many features
https://stanfordnlp.github.io/stanza/models.html

that has a chinese (simplified) model and provides dep-parser, lemma and other basic NLP features.

I'm a bit confused as it uses spacy for tokenization:
https://stanfordnlp.github.io/